Meaningful collaboration for responsible innovation

Many innovative businesses have discovered an added value in collaborating with experts, users or other stakeholders in developing innovative products or services. Not all collaboration with stakeholders, however, corresponds to the criteria for opening up an innovation process to the needs of societal actors under the terms of responsible innovation. The question of what makes collaboration meaningful in the sense of responsible innovation was presented and discussed in a 75 min workshop at the European Science Open Forum (ESOF) in Toulouse, France in June 2018. Identified success factors and challenges for making a collaboration process meaningful for the collaborating parties highlight the importance of competent process preparation and facilitation, investment of time and effort to enable mutual understanding and the development of trustful relationships as well as the collaborating partners' willingness to implement changes that result from the collaboration process

Modeling the dispersion of Ambrosia artemisiifolia L. pollen with the model system COSMO-ART

Common ragweed (Ambrosia artemisiifolia L.) is a highly allergenic plant that is spreading throughout Europe. Ragweed pollen can be transported over large distances by the wind. Even low pollen concentrations of less than 10 pollen m−3 can lead to health problems in sensitive persons. Therefore, forecasting the airborne concentrations of ragweed pollen is becoming more and more important for public health. The question remains whether distant pollen sources need to be considered in reliable forecasts. We used the extended numerical weather prediction system COSMO-ART to simulate the release and transport of ragweed pollen in central Europe. A pollen episode (September 12–16, 2006) in north-eastern Germany was modeled in order to find out where the pollen originated. For this purpose, several different source regions were taken into account and their individual impact on the daily mean pollen concentration and the performance of the forecast were studied with the means of a 2 × 2 contingency table and skill scores. It was found that the majority of the pollen originated in local areas, but up to 20% of the total pollen load came from distant sources in Hungary. It is concluded that long-distance transport should not be neglected when predicting pollen concentrations

Regional Impact of Snow‐Darkening on Snow Pack and the Atmosphere During a Severe Saharan Dust Deposition Event in Eurasia

Light-absorbing impurities such as mineral dust can play a major role in reducing the albedo of snow surfaces. Particularly in spring, deposited dust particles lead to increased snow melt and trigger further feedbacks at the land surface and in the atmosphere. Quantifying the extent of dust-induced variations is difficult due to high variability in the spatial distribution of mineral dust and snow. We present an extension of a fully coupled atmospheric and land surface model system to address the impact of mineral dust on the snow albedo across Eurasia. We evaluated the short-term effects of Saharan dust in a case study. To obtain robust results, we performed an ensemble simulation followed by statistical analysis. Mountainous regions showed a strong impact of dust deposition on snow depth. We found a mean significant reduction of −1.4 cm in the Caucasus Mountains after 1 week. However, areas with flat terrain near the snow line also showed strong effects despite lower dust concentrations. Here, the feedback to dust deposition was more pronounced as increase in surface temperature and air temperature. In the region surrounding the snow line, we found an average significant surface warming of 0.9 K after 1 week. This study shows that the impact of mineral dust deposition depends on several factors. Primarily, these are altitude, slope, snow depth, and snow cover fraction. Especially in complex terrain, it is therefore necessary to use fully coupled models to investigate the effects of mineral dust on snow pack and the atmosphere

Mapping and managing productive organizational energy over time: The Energy Pattern Explorer tool

To strategically manage the deployment of collective human resources toward performance, managers must recognize, interpret, and align the volatile resources of productive organizational energy. Despite relevant prior work, research and practice still lack a comprehensive approach toward analyzing and managing energy patterns over time. We develop a framework for temporal configurations and prototypical trajectories of productive organizational energy. We then introduce the ‘Energy Pattern Explorer’ as a strategy tool to: (1) identify and predict actual patterns of productive organizational energy in organizations, and (2) suggest energy leadership activities specific to current and anticipated changes and patterns of productive organizational energy. We provide examples of how managers can use this tool and conclude with suggestions for research and practice

Contrails and their impact on shortwave radiation and photovoltaic power production – a regional model study

A high-resolution regional-scale numerical model was extended by a parameterization that allows for both the generation and the life cycle of contrails and contrail cirrus to be calculated. The life cycle of contrails and contrail cirrus is described by a two-moment cloud microphysical scheme that was extended by a separate contrail ice class for a better representation of the high concentration of small ice crystals that occur in contrails. The basic input data set contains the spatially and temporally highly resolved flight trajectories over Central Europe derived from real-time data. The parameterization provides aircraft-dependent source terms for contrail ice mass and number. A case study was performed to investigate the influence of contrails and contrail cirrus on the shortwave radiative fluxes at the earth’s surface. Accounting for contrails produced by aircraft enabled the model to simulate high clouds that were otherwise missing on this day. The effect of these extra clouds was to reduce the incoming shortwave radiation at the surface as well as the production of photovoltaic power by up to 10 %

Quantitative DNA Analyses for Airborne Birch Pollen

Birch trees produce large amounts of highly allergenic pollen grains that are distributed by wind and impact human health by causing seasonal hay fever, pollen-related asthma, and other allergic diseases. Traditionally, pollen forecasts are based on conventional microscopic counting techniques that are labor-intensive and limited in the reliable identification of species. Molecular biological techniques provide an alternative approach that is less labor-intensive and enables identification of any species by its genetic fingerprint. A particularly promising method is quantitative Real-Time polymerase chain reaction (qPCR), which can be used to determine the number of DNA copies and thus pollen grains in air filter samples. During the birch pollination season in 2010 in Mainz, Germany, we collected air filter samples of fine (<3 μm) and coarse air particulate matter. These were analyzed by qPCR using two different primer pairs: one for a single-copy gene (BP8) and the other for a multi-copy gene (ITS). The BP8 gene was better suitable for reliable qPCR results, and the qPCR results obtained for coarse particulate matter were well correlated with the birch pollen forecasting results of the regional air quality model COSMO-ART. As expected due to the size of birch pollen grains (~23 μm), the concentration of DNA in fine particulate matter was lower than in the coarse particle fraction. For the ITS region the factor was 64, while for the single-copy gene BP8 only 51. The possible presence of so-called sub-pollen particles in the fine particle fraction is, however, interesting even in low concentrations. These particles are known to be highly allergenic, reach deep into airways and cause often severe health problems. In conclusion, the results of this exploratory study open up the possibility of predicting and quantifying the pollen concentration in the atmosphere more precisely in the future

Lessons Learned from an Outbreak in Germany, 2012-2013

Background We undertook investigations in response to an invasive meningococcal disease (IMD) outbreak in men who have sex with men (MSM) in Berlin 2012–2013 to better understand meningococcal transmission and IMD risk in MSM. Methods We retrospectively searched for further IMD cases in MSM in Germany through local health departments and undertook exploratory interviews. We performed antigen sequence typing, characterized fHbp and aniA genes of strains with the outbreak finetype and reviewed epidemiologically or spatiotemporally linked cases from 2002–2014. Results Among the 148 IMD-cases notified from 01.01.2012–30.09.2013 in 18–59 year-old men we identified 13 MSM in 6 federal states: 11 serogroup C (MenC, all finetype C:P1.5–1,10–8:F3-6), 2 MenB. Interviews with 7 MSM revealed frequent meeting of multiple partners online or via mobile apps and illicit drug use as potential risk factors. MenC incidence was 13-fold higher in MSM than non-MSM. MenC isolates from 9/11 MSM had a novel fHbp allele 766. All C:P1.5–1,10–8:F3-6 strains from MSM versus 16/23 from non-MSM had intact aniA genes (p = 0.04). Although definitive evidence for transmission among MSM in epidemiological or spatiotemporal clusters in 2002–2014 was lacking, clusters were more frequent in men aged 20–49 years. Molecular analysis of C:P1.5–1,10–8:F3-6 strains revealed cases with intact aniA since 2007, mainly associated with fHbp361, fHbp766 and fHbp813, all involving one or more MSM. Conclusions MenC incidence was elevated in MSM during the study period. Multiple casual sexual contacts and illicit drug use were common in affected MSM. In all strains from MSM we detected an intact aniA gene coding for a nitrite reductase, which permits survival in microanaerobic environments and could play a role in meningococcal transmission in MSM through urogenital colonization. Furthermore, meningococcal transmission among MSM may be sustained over large areas and thus require modified spatiotemporal scanning algorithms for timely detection and control

Spatiotemporal Analysis of Invasive Meningococcal Disease, Germany

Meningococcal disease clustering was found by DNA sequence–based finetyping and cluster detection software